Method and system for determining fluid status based on a dynamic impedance surrogate for central venous pressure

ABSTRACT

A method and system are provided for determining fluid status with a central venous system of a heart. Dynamic impedance (DI) data and static impedance (SI) data are collected over multiple cardiac cycles (CC) for a persistent time period of interest (POI). The DI and SI data are collected along a central venous (CV) vector that extends through a superior vena cava (SVC). The DI and SI data are analyzed to obtain DI long-term variation (LTV) information and SI LTV information, respectively, and to detect whether the DI LTV information and the SI LTV information include decreasing persistent trends in the DI and SI data. When decreasing persistent trends are detected in the DI and SI data, an overload output is generated to indicate that the heart is experiencing a volume overload state. The DI and SI data represent a surrogate for central venous pressure.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is related to U.S. patent application Ser. No. 13/841,184, filed Mar. 15, 2013, titled “METHOD AND SYSTEM FOR CHARACTERIZING CARDIAC FUNCTION BASED ON DYNAMIC IMPEDANCE.”

FIELD OF THE INVENTION

Embodiments of the present invention generally relate to determining fluid status, and more particularly to methods and systems that utilize dynamic impedance as a surrogate for central venous pressure to determine fluid status.

BACKGROUND OF THE INVENTION

Implantable medical devices (IMDs) exist today that are used to monitor venous volume status. These conventional IMDs utilize an impedance measurement taken along a RV vector between the RV-tip electrode and the CAN electrode and along a vector between the RV coil to CAN electrodes. The duration and magnitude of decreases in impedance measured along the RV-tip—CAN and RV-coil to CAN vectors is used to detect volume overload. These RV vectors use weighted combinations of impedance measured along the RV-tip to CAN and RV-coil to CAN vectors. Specificity is improved by using multiple vectors and by including the duration of the impedance change.

Impedance measurements obtained over a cardiac cycle generally include two components, namely a DC (or static) component and an AC (or dynamic) component. The DC or static component generally remains fixed, throughout an individual cardiac cycle, for a given posture. The DC impedance component will remain constant beyond a single cardiac cycle. However, in patients with heart disease, significant changes in the DC component may take place over longer periods of time, such as over several hours, days or weeks.

The dynamic or AC impedance component changes periodically throughout each heartbeat. Conventional IMDs, that measure impedance, generally separate the dynamic AC component from the DC component by applying a high pass filter to the overall impedance measurement. Heretofore, conventional IMDs discard the AC or dynamic impedance component and do not use the dynamic impedances waveforms. Instead, conventional IMDs use only the DC impedance because conventional IMDs are only concerned with the overall DC impedance that is representative of the impedance attributable to tissue.

However, conventional IMDs have not been able to determine fluid status in the central venous system. For example, when patients experience excessive pressure buildup in the central venous system, the SVC, IVC and/or RA may enlarge over time, which is referred to as “volume overload”. Yet, the overall DC impedance does not exhibit satisfactory specificity or sensitivity as an indicator of the presence of volume overload.

Today, the operations to configure a pacemaker are often performed by selecting a desired lead location for a specific patient (e.g., septal vs. apical) and then programming the parameter settings of the pacemaker, such as the AV and/or VV delay, the rate responsive AV and/or VV delay and other parameters known in the field. Today, the operations to configure a cardiac resynchronization therapy (CRT) configuration are similarly performed by selecting a desired lead location (e.g., by avoiding infarct zones, reduced dyssynchrony, LV apical vs. septal) and then programming the CRT device with desired AV and VV delays. The AV delay and VV delay are selected traditionally by physicians through the use of an echocardiography evaluation. However, the echocardiography evaluation is time consuming and has high variations.

Thus, these conventional selection methods currently utilize timing features (conduction delay, dyssynchrony measures), systemic hemodynamic measures (Stroke volume, pre-load) and echocardiography evaluation bases measures of cardiac function for determining ejection time, myocardial performance index, left ventricular end systole volume, and left ventricular end diastole volume.

However, it is preferred to tailor each device to the individual patient's underlying etiology and functional status. Yet, a comprehensive echocardiography evaluation assessment is time consuming. Also, when the parameters of a pacemaker are set to a preferred setting, while a patient is in the clinic, the same parameter settings may not reflect the best parameter settings for the patient when the person is ambulatory and active.

SUMMARY

In accordance with embodiments herein, a method is provided for determining fluid status with a central venous system of a heart. The method comprises collecting dynamic impedance (DI) data and static impedance (SI) data over multiple cardiac cycles (CC) for a persistent time period of interest (POI). The DI and SI data is collected using an impedance vector that crosses the central venous (CV) section, where the impedance vector is referred to as a “central venous or CV vector” that extends through a superior vena cava (SVC). The method further includes analyzing the DI and SI data, collected over the persistent time POI, to obtain DI long-term variation (LTV) information and SI LTV information, respectively, and detecting whether the DI LTV information and the SI LTV information include decreasing persistent trends in the DI and SI data. When decreasing persistent trends are detected in the DI and SI data, the method generates an overload output indicating that the heart is experiencing a volume overload state. The DI and SI data represent a surrogate for central venous pressure such that when a decreasing persistent trend is detected a fluid status corresponds to the volume overload state. The overload output indicates that an interior dimension of the SVC is expanding over the LT time period of interest.

Optionally, the analyzing operation may further comprise analyzing at least one morphologic characteristic from the DI data and an average of SI data to obtaining DI and SI central venous (CV) indicators for each cardiac cycle, the DI and SI CV indicators representative of a feature of interest within the DI and SI data, respectively; and analyzing the DI and SI indicators to obtain the LTV information. Optionally, the DI LTV information may correspond to changes in dynamic impedance over the persistent time period of interest that extends over at least one of hours, days or weeks.

Optionally, the method may further comprise analyzing the DI and SI data, collected over a transient time period of interest, to obtain DI short-term variation (STV) information and determining whether the DI STV information includes an increasing or decreasing ST trend in the DI data. When a decreasing ST trend exists in the DI data, the method generates a stroke volume (SV) output indicating that the heart is experiencing a decrease in stroke volume.

Optionally, the method further comprises changing at least one IMD therapy parameter setting, over multiple cardiac cycles, and repeating the collecting, analyzing and detecting operations to obtain a collection of DI LTV information and the SI LTV information associated with different IMD therapy parameter settings. Based on the overload output, the method determines a select level for the at least one IMD therapy parameter setting that provides at least one of i) heart rate paced, ii) pacing mode (options include DDD, DOO, VVI, VOO, AAI and AOO), iii) a select peak to peak amplitude, iv) a select minimum amplitude, v) a select DI change per unit time (dZ/dt), vi) a select slope, vii) a select ventricular filling time, or viii) a select ventricular emptying time, of the DI data when plotted over time. Optionally, the collecting of DI data may include utilizing an IMD case electrode and at least one of an SVC electrode, an IVC electrode and an RA electrode to define the CV vector and to collect the DI and SI data. Optionally, the analyzing the DI data may include determining, as a morphologic characteristic, at least one of i) a peak to peak (P-P) amplitude, ii) a minimum amplitude, iii) a minimum DI change per unit time (dZ/dt), and iv) slope of the DI data over the CC.

The CV vector may include at least one of the SVC, RA or IVC electrodes of the IMD system and is preferred to cover the pulmonary artery section, then extends through other electrodes of the IMD system.

In accordance with at least one embodiment, a system is provided for determining fluid status within a central venous system of a heart. The system comprises inputs that are configured to receive dynamic impedance (DI) data and static impedance (SI) data that is collected over multiple cardiac cycles (CC) for a persistent time period of interest (POI). The DI and SI data are collected along a central venous (CV) vector that extends through a superior vena cava (SVC). The system includes an impedance analysis module configured to analyze the DI and SI data, collected over the persistent time POI, to obtain DI long-term variation (LTV) information and SI LTV information, respectively. The system includes a trend detection module configured to detect when the DI LTV information and the SI LTV information include decreasing persistent trends in the DI and SI data, the trend detection module configured to generate an overload output indicating that the heart is experiencing volume overload when the trend detection module detects the decreasing persistent trend in the DI and SI data. The DI and SI data represent a surrogate for central venous pressure such that when the trend detection module detects the decreasing persistent trend, a fluid status in the CV system corresponds to a volume overload state. The overload output indicates that an interior dimension or distensibility of the SVC is expanding over the LT time period of interest by more than a predetermined CV expansion threshold.

Optionally, the analysis module may be further configured to preprocess the impedance waveforms interested and analyze at least one morphologic characteristic from the DI and SI data to obtaining DI and SI central venous (CV) indicators for each cardiac cycle, the DI and SI CV indicators representative of a feature of interest within the DI and SI data, respectively; and analyze the DI and SI indicators to obtain the LTV information.

The DI LTV information corresponds to changes in dynamic impedance over the persistent time period of interest that extends over at least one of hours, days or weeks.

The analysis module may be further configured to analyze the DI and SI data, collected over a transient time period of interest, to obtain DI short-term variation (STV) information; and the trend detection module is further configured to determine whether the DI STV information includes an increasing or decreasing ST trend in the DI data, when a decreasing ST trend exists in the DI data, the trend detection module configured to generate a stroke volume (SV) output indicating that the heart is experiencing a decrease in stroke volume.

Optionally, the system comprises a therapy control module configured to change changing at least one IMD therapy parameter setting, over multiple cardiac cycles, and repeat the collecting, analyzing and detecting operations to obtain a collection of DI LTV information and the SI LTV information associated with different IMD therapy parameter settings. The therapy control module may be configured to determine, based on the overload output, a select level for the at least one IMD therapy parameter setting that provides at least one of i) a select peak to peak amplitude, ii) a select minimum amplitude, iii) a select DI change per unit time (dZ/dt), iv) a select slope, v) a select ventricular filling time, or vi) a select ventricular emptying time, of the DI data when plotted over time, vii) heart rate and viii) pacing modes. The system further comprises a lead coupled to the inputs, where the lead includes an IMD case electrode and at least one of an SVC electrode, an IVC electrode and an RA electrode to define the CV vector and to collect the DI and SI data.

Optionally, the analysis module may be configured to analyze the DI data by determining, as a morphologic characteristic, at least one of i) a peak to peak (P-P) amplitude, ii) a minimum amplitude, iii) a minimum DI change per unit time (dZ/dt), and iv) slope of the DI data over the CC, v) area under the curve, vi) time features from above fiducial points The analysis module may be configured to receive patient state information indicating at least one of a select activity state and a select posture position of a patient, and to control the inputs to collect the DI data only when the patient state information satisfies a patient state threshold.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates a simplified diagram of an implantable medical IMD in electrical communication with leads implanted in or proximate a patient's heart in accordance with an embodiment.

FIG. 1B illustrates a flow chart for determining cardiac fluid status in accordance with an embodiment by one or more of an IMD, external programmer and system described herein.

FIG. 1C illustrates a process carried out in connection with determining fluid status in the CV system in accordance with an embodiment.

FIG. 2 illustrates a cylindrical model of the SVC and the surrounding tissue with a shocking coil located in the middle of the cylinder.

FIG. 3 illustrates an example of how static or DC impedance, Zo, behaves with progressive volume overload as the SVC diameter (or more generally SVC volume) increases.

FIG. 4 illustrates a graph modeling a behavior of the SVC with changes in volume overload while holding stroke volume constant.

FIG. 5 illustrates graphs modeling a behavior of stroke volume for different fixed/constant SVC diameters (corresponding to different constant volume overloads.

FIG. 6 illustrates a block diagram of an IMD configured to implement the methods described herein to characterize cardiac function in accordance with an embodiment.

FIG. 7 illustrates a functional block diagram of the external device that is operated in accordance with the processes described herein and to interface with implantable medical devices as described herein.

FIG. 8 shows an impedance waveform detected over one cardiac cycle with examples of the dynamic VRI denoted thereon in accordance with an embodiment.

DETAILED DESCRIPTION

Embodiments herein concern systems and methods that utilize new dynamic impedance vectors and combinations of the dynamic and static impedance data to increase specificity for detecting volume overload within CV system of a heart. Embodiments herein concern systems and methods that use the dynamic impedance to increase specificity and sensitivity. Dynamic impedance may also be referred to as cardiogenic impedance, because the dynamic AC waveform is periodic with changes associated with the motion of the heart.

Embodiments herein collect dynamic and static impedance information that has greater sensitivity, relative to other impedance vectors, to central venous blood pressure using CV vectors that cross the pulmonary artery section. For example, vectors that are very sensitive to dynamic impedance, associated with the central venous system, extend between the CAN electrode and one or more electrodes in the SVC, RA and/or IVC. The CAN-SVC, RA and/or IVC vectors are highly sensitive to dynamic impedance of the central venous system because the greater vessels act as a reservoir for blood. In fact, at least one echocardiographic study has shown that the diameter of the IVC increases dramatically with central venous pressure.

The SVC to case dynamic impedances provide periodic, AC coupled impedance-gram changes with each heartbeat. Recent investigations and mathematical modeling have provided insight regarding the mechanism of impedance modulation. During systole, the impedance (along a vector through the SVC, RA or IVC) decreases because blood from venous return accumulates in the SVC and right atria. The additional blood increases the dimension of the SVC and the right atrium. Given that blood is more conductive than tissue, as the SVC or RA expands, the impedance (as measured by electrodes in the SVC, IVC or RA) lowers.

During diastole, the blood drains from the vena cava and right atrium into the RV and decreases venous blood volume. As the blood volume in the SVC, RA and IVC decreases, the impedance (as measured by electrodes in the SVC, IVC and RA) increases. Hence, the SVC to case cardiogenic impedance drops during systole and increases during diastole, which is unlike the behavior of cardiogenic impedance changes that are measured along a vector that extends to/from an electrode(s) in one or more ventricles. Intra-ventricular cardiogenic impedance behaves in an opposite direction as compared to cardiogenic impedance measured along a vector that extends through the SVC, RA and/or IVC. Intra-ventricular cardiogenic impedance increases during systole and decreases during diastole. For example, intra-ventricular cardiogenic impedance may be measured along a vector extending between RV coil to case electrodes.

Next, it should be considered how these impedance vectors change during blood volume changes. Beginning with SVC to case dynamic impedance behaviors, as described herein the amplitude of the DI waveform is modulated by blood removal from the venous system. For a fixed venous blood volume, the amplitude of the cardiogenic impedance is related to the change in venous volume attributable to filling and emptying of the heart. Another way of describing this is that the amplitude of the SVC to case cardiogenic impedance is related to stroke volume. Rather than looking at stroke volume from the output of the heart at the aorta or pulmonary artery, the decrease of the venous volume with blood filling the heart and restoring venous blood volume from venous return modulates the SVC to case cardiogenic impedance. Next, consider what happens to the amplitude of the cardiogenic impedance as blood is added to the central venous volume. For a constant stroke volume, the amplitude of the cardiogenic venous impedance is modulated by the size of the SVC to case impedance.

When a patient's physiologic condition deteriorates, the heart begins to experience venous overload. Venous overload, in part, represents an increase in blood pressure in the SVC and IVC. As the blood pressure increases in the SVC and IVC, the amount of blood in the SVC and IVC similarly increases. As the volume of blood is increased with overload, the relative percentage of blood removed from the venous reservoir with each stroke volume decreases because continuous reservoir volume increases. Hence, the average volume of blood that remains in the SVC, RA and IVC at all times increases.

With the foregoing general principles in mind, next the discussion turns to exemplary embodiments in accordance with the inventions disclosed herein.

FIG. 1A illustrates a simplified diagram of an implantable medical IMD 10 in electrical communication with three leads 20, 21 and 30 implanted in or proximate a patient's heart 12 for delivering single or multi-chamber stimulation (e.g. pacing, ATP therapy, high voltage shocks and the like) and for characterizing cardiac function according to an embodiment. The stimulation may include pacing pulses that are delivered along one or more pacing vectors. Optionally, the stimulation may include ATP pulses or a high voltage shock that is delivered along one or more ATP therapy vectors, cardioverter vectors or defibrillation vectors. The implantable medical IMD 10 may be a pacing device, a pacing apparatus, a cardiac rhythm management device, an implantable cardiac stimulation device, an implantable cardioverter/defibrillator (ICD), a cardiac resynchronization therapy (CRT) device, a monitoring device and the like. The IMD 10 is programmable, by an operator, to set certain operating parameters, as well as therapy-related parameters. The IMD 10 is configured to operate with various configurations of leads. The IMD 10 is configured to sense various types of information and deliver various types of therapies. For example, the IMD 10 may sense intracardiac electrogram signals, impedances and the like.

In FIG. 1A, the IMD 10 is coupled to an RA lead 20 having at least an atrial tip electrode 22, which typically is implanted in the patient's right atrial appendage. The IMD 10 is coupled to an LV lead 21 that includes various electrodes, such as an LV tip electrode 23, intermediate LV electrodes 24-26, and LA electrodes 27-28. The LV lead 21 may sense atrial and ventricular cardiac signals and impedances and deliver left ventricular therapy using the LV tip electrode 23, the intermediate LV electrodes 24-26, and the LA electrodes 27 and 28. Left atrial therapy uses, for example, first and second LA electrodes 27 and 28. The LV and LA electrodes 23-28 may be used as sensing sites, where cardiac signals and/or impedances are sensed, and/or may be used as pacing and/or shock therapy sites. A right ventricular lead 30 may include one or more of an RV tip electrode 32, an RV ring electrode 34, and a superior vena cava (SVC) coil electrode 38 (also known as a RA coil electrode). The right ventricular lead 30 is capable of sensing cardiac signals and/or impedances, and delivering stimulation in the form of pacing and shock therapy to the SVC and/or right ventricle.

Optionally, more or fewer electrodes may be utilized. The LV electrodes may be separated further apart or positioned closer to one another. Optionally, all or a portion of the LV electrodes may be shifted along the LV lead 21 until positioned proximate to the mitral valve, aortic valve, or the left atrial ports to/from the pulmonary veins. The LV lead 21 may be inserted directed into the LV chamber or inserted into a vein or artery extending along the heart wall proximate to the left ventricle. Optionally, the LV lead 21 may be coupled to a patch or mesh net electrode that is secured to or located adjacent to an exterior wall of the left ventricle and/or the left atrium.

Embodiments are described herein, whereby multiple electrodes are utilized to sense impedance along multiple sensing vectors in order to measure local impedance information along the select sensing vectors. Impedance measurements collected along the select sensing vectors are utilized to derive dynamic impedance data correlated to one or more cardiac functions.

The IMD 10 defines sensing vectors between various combinations of two or more electrodes 22-28, 32, 34 and 38, and the housing of the IMD 10. FIG. 1A illustrates examples of sensing vectors 149-155. The IMD 10 obtains one or more impedance measurements along the select one or more sensing vectors 149-155 which extend through a substantial majority of the portion of the heart or vessels of interest. An individual measurement of impedance includes components associated with the impedance of the walls of the heart 12, the blood in the heart 12 and any external tissue or muscle through which the corresponding active sensing vector extends.

The sensing vector 149 extends between the SVC coil electrode 38 and the CAN electrode of the IMD 10. The sensing vector 150 extends between the RA electrode 22 and the RV electrode 34. The sensing vector 151 extends between the RV electrode 34 and the LV electrode 25. The sensing vector 152 extends between the LV electrode 25 and the RA electrode 22. The sensing vector 153 extends between the RV electrode 34 and the CAN electrode of the IMD 10. The sensing vector 154 extends between the LV electrode 25 and the CAN electrode. The sensing vector 155 extends between the RA electrode 22 and the CAN. Optionally, alternative and/or additional electrodes may be used to form alternative and/or additional sensing vectors.

Each LV and RV electrode 22-38 represents a potential sensing site and/or therapy site. When functioning as a sensing site, the corresponding LV and/or RV electrode sense signals that are utilized to obtain impedance measurements. The sensing sites differ based on the type of device and type of detection algorithm utilized.

For example, in a CRT-D type device, when utilizing the PE algorithm, the device utilizes sensing vectors that extend between the RV coil electrode and CAN, and between a LV ring electrode and the CAN. In an ICD type device, when utilizing the PE algorithm, the device utilizes sensing vectors that extend between the RV coil electrode and the CAN and between the RV ring electrode and the CAN. In a CRT-P type device, when utilizing the PE algorithm, the device utilizes sensing vectors that extend between the LV ring electrode and the CAN, between the RA ring electrode and the CAN, and between the RV ring electrode and CAN. In a pacemaker type device, the device generally utilizes an active sensing vector that extends between the RV ring electrode and the CAN.

The impedance measured along the sensing vectors 149-155 may be expressed in terms of ohms. Alternatively, the impedance may be expressed as an admittance measurement. The admittance may be inversely related to the impedance. The impedance measured along the sensing vectors 149-155 may vary based on a variety of factors, including the amount of fluid in one or more chambers of the heart 12 and/or thoracic space. As a result, the impedance measurement may be indicative of central venous pressure (CVP). As more blood fills the RA, SVC and IVC, the CVP increases. Blood is more electrically conductive than the myocardium of the heart 12. Consequently, as the amount of blood in the RA, SVC and IVC increases, the CVP increases and the impedance measured along the active sensing vector decreases. Conversely, decreasing CVP may result in the impedance measurement increasing as there is less blood in the RA, SVC and IVC.

Optionally, impedance measurements along various sensing vectors may be utilized to monitor and characterize pressure and blood flow in other chambers of the heart, such as RA, RV, LA and/or LV pressure and blood flow.

FIG. 1B illustrates a method for determining cardiac fluid status in accordance with an embodiment by one or more of an IMD, external programmer and system described herein. The method of FIG. 1B begins with the therapy parameters of the IMD 10 set to predetermined values and/or set manually, or automatically by the IMD, based on conventional programming techniques. The IMD therapy parameters may include one or more of AV delay, VV delay, pacing electrode combination, pacing pulse width, strength, interval and the like.

Beginning at 102, the method determines a patient state. For example, the patient state may represent the patient's posture position (e.g., lying down, standing up, sitting). Optionally, the patient state may represent a level of physical exertion that the patient is undergoing. For example, the patient may be exercising, at rest, sleeping, walking, climbing, and the like. As one example the method may determine the patient state in connection with determining whether, and to what extent, to use dynamic and static impedance data that is obtained while in the present patient state.

For example, at 102, the method may determine whether the patient is in a state in which dynamic impedance data, if acquired, would substantially correlate to the cardiac function of interest. For example, when the patient state indicates that the patient is experiencing an excessively high heart rate, the method may determine to cease operation for a period of time or a predetermined number of cardiac cycles. When the patient is undergoing heavy excursion, the DI data may not substantially track or correlate to certain cardiac functions as closely as desired. The degree to which DI data is expected to track or correlate to a cardiac function of interest (CFI) may be characterized in terms of variance, deviation and the like.

At 104, the method collects cardiac signals associated with electrical behavior of a heart over at least one cardiac cycle while an IMD operates based on current IMD therapy parameter settings. For example, the cardiac signals may be intra-cardiac electrogram (IEGM) signals, EKG signals, and the like. The cardiac signals may be collected from external skin electrodes, the implanted electrodes 22-38 (along one or more of sensing vectors 149-155) and the like. The cardiac signals may be indicative of mechanical behavior, such as from an accelerometer or other sensor that determines an amount of activity and/or an orientation of the patient. The cardiac signals may indicate mechanical behavior such as exercise, climbing stairs, walking, laying in a prone or supine position, sitting up-right, standing, and the like.

At 104, the method identifies a timing feature of interest (FOI) from the cardiac signals. For example, the timing feature of interest may be the peak of the R-wave, the start or center of the P-wave, the ST segment, and the like. The timing feature may be intrinsic (e.g., a naturally occurring cardiac event) or paced (e.g., a paced R-wave, a paced P-wave, etc.). When the cardiac signal is indicative of mechanical behavior, the timing feature of interest may represent the amount of movement (indicative of exercise), the orientation of the patient with respect to gravity (prone, supine, standing, etc.) and the like.

At 106, the method collects dynamic impedance (DI) data and static impedance (SI) data for a collection window over at least one cardiac cycle (CC) along at least one vector of interest, such as a venous return (VR) vector. The VR vector may be aligned such that changes in the DI data substantially correlate with changes in CFI, such as the volume of the SVC, RA and/or IVC. For example, the VR vector may extend through at least one of the SVC, RA or IVC. For example, the collecting operation may collect the DI and SI data along a VR vector that is defined by an IMD case electrode and at least one of an SVC electrode, an IVC electrode and an RA electrode. The select combination of electrodes defines the VR vector used to collect the DI and SI data. Optionally, different electrode combinations may be used to collect subsets of the DI and SI data, where each subset of DI and SI data may be analyzed for a common, or for different, morphologic characteristics, where the subsets of DI and SI data collectively track the CFI.

Current flux density at the surface of the SVC electrode (e.g., or IVC electrode or RA electrode) is relatively high as compared to the current flux density remote from the SVC electrode (e.g., at other chambers of the heart or outside of the heart or at the case electrode). Due to the substantially larger current flux density immediately adjacent the SVC electrode, the DI and SI data are primarily affected by changes in the impedance in the area (e.g., the blood) immediately surrounding the SVC electrode, while changes in the impedance in areas more remote from the SVC electrode have less relative impact on changes in the dynamic impedance.

As one example, the dynamic impedance data may be recorded from an anode-cathode combination that delivers a reference current between a SVC coil electrode and a case electrode, while measuring voltage between the same or different SVC coil and case electrodes.

At 108, the method analyzes the DI and SI data to obtain a dynamic venous return indicator (VRI) and a static VRI. The dynamic VRI may represent a peak to peak change in the dynamic impedance (P-P dZ), a duration of the time interval between the positive peak and negative peak (P-P dZ duration), min Z, dZ/dt, area under the curve and the like. FIG. 8 shows an impedance waveform detected over one cardiac cycle with examples of the dynamic VRI denoted thereon. For example, FIG. 8 illustrates the maximum and minimum DI (MaxZ and Min Z) from which the peak to peak change (P-P dZ) and timer interval (P-P dZ duration) are measured. FIG. 8 further illustrates the maximum and minimum change in DI (MindZ/dt and Max dZ/dt) which may represent features of interest. FIG. 8 also illustrates various time intervals of interest such as the time interval between the maximum and minimum DI values (Delta-Z-time), the time intervals from the start of the cardiac cycle (at time 0) until the maximum and minimum changes in slope (Max dZ/dt time and Min dZ/dt time), and the timer intervals from the start of the cardiac cycle until the maximum and minimum DI values (Max Z time and Min Z time) and the like.

The static VRI may represent the D.C. or impedance offset (relative to zero or some other reference impedance) as measured over a select period of time. For example, a reference impedance may be established during a clinical appointment and the SI data measurements taken relative to the reference impedance.

At 110, the dynamic and static VRI are saved along with information of interest regarding the patient state, time of day, etc. For example, the method may save the patient's posture position, IMD therapy parameter settings, time of day, heart rate, arrhythmias detected, other cardiac related information and the like.

At 112, the method determines whether to repeat 102 to 110 again while maintaining the IMD therapy parameters constant. For example, it may be desirable to obtain a predetermined number of DI and SI data measurements, representing a DI data subset and an SI data subset, while holding constant the IMD therapy parameter settings. Optionally, it may be desirable to obtain a certain number of DI and SI data measurements, to form a DI data subset and a SI data subset, while i) the patient is in a given posture, ii) within a certain heart rate range, or iii) at the same time of day, while maintaining a common or constant IMD therapy parameter setting. Optionally, it may be desirable to obtain a new subset of DI and SI data at fixed or variable periods over a short period of time, such as every cardiac cycle over a 1 minute, 5 minute, 20 minute period of time, etc., all while utilizing the same IMD therapy parameter settings.

The operations at 102-110 are repeated until, at 112, it is determined that the desired amount of DI and SI data for the subset associated with the current IMD therapy parameter settings. Once the desired number of measurements of DI and SI data is collected (and the associated dynamic and static VRI are determined) flow moves to 114.

At 114, the method determines whether the operations at 102-110 should be repeated with new IMD therapy parameter settings. For example, it may be desirable to obtain a select number (e.g., 5, 10, 20) of sets of DI and SI data subsets, where each DI and SI data subset is associated with different IMD therapy parameter settings. Optionally, it may be desirable to obtain a set of DI and SI data where each DI and SI data subset is collected periodically over a long period of time, such as a DI and SI data subset every 20 minutes, every hour, every day, weekly and the like, all while utilizing the same or different IMD therapy parameter settings. When, at 114, it is determined that more DI and SI data should be collected at a different IMD therapy parameter setting, flow moves to 116.

At 116, the method changes (modulates) at least one IMD therapy parameter setting. Examples of IMD therapy parameters that may be adjusted include the AV delay, the VV delay, the pacing pulse amplitude, the pacing pulse duration, pacing pulse interval, electrode configuration, pacing pulse vectors, and the like. Once the IMD therapy parameters are modified, the operations at 102 to 112 are repeated.

Optionally, the decision at 112 may be removed and the operations at 102-110 performed only once for each IMD therapy parameter setting.

The operations at 102-112 are repeated until, at 114, it is determined that the desired number of sets of DI and SI data subsets, and the related dynamic and static VRI are collected for a corresponding number different IMD therapy parameter settings. Next, once the desired number of sets of DI and SI data is collected (and the associated dynamic and static VRI are determined) flow moves to 114. Thereafter, flow moves from 114 to 118.

At 118, the method determines the fluid status in the central venous system. For example, fluid status may include determining whether the heart is experiencing volume overload. The operations performed at 118 are discussed below in more detail in connection with FIG. 1C.

FIG. 1C illustrates a process carried out in connection with determining fluid status in the CV system in accordance with an embodiment. At 180, the method obtains, from memory, saved dynamic and static VRI values from one or more select periods of time. As one example, the dynamic and static VRI values may be calculated in accordance with the method of FIG. 1B. At 180, additional saved information may be obtained from memory as well, such as the time of data, heart rate, patient state and the like, associated with each dynamic and static VRI value. It should be recognized that the DI and SI data collection and analysis process of FIG. 1B may continuously operate such that new DI and SI data (and associated dynamic and static VRI) is collected independent of when the fluid status determination operations of FIG. 1C are performed. For example, dynamic and static VRI may be stored for a predetermined period of time or until a predetermined amount of data and information is stored. Once, the predetermined period of time or amount of data is exceeded, then the oldest DI and SI data (and oldest dynamic and static VRI) are deleted to make room in memory for new DI and SI data (and dynamic and static VRI). As a further option DI and SI data may not be saved after the related dynamic and static VRI are calculated. Instead, once the dynamic and static VRI are calculated, the underlying DI and SI data may be deleted at that point.

At 182, the method analyzes the dynamic and static VRI over a select long or persistent time period of interest (POI) to obtain long-term variation (LTV) or persistent variation information regarding changes and trends in the DI and SI data. The long or persistent time POI is chosen to be sufficient in length that a characteristic of interest in the cardiac behavior will manifest itself and remain apparent through changes in the DI and SI data over the chosen period of time. For example, the long or persistent period of time may be an hour, a day, a week and the like.

At 184, the method analyzes the LTV information to determine whether long-term trends are indicated. For example, the LTV information may indicate that, over a two-week period, the patient's dynamic and static impedance have both been decreasing. When the patient's dynamic and static impedance both decrease over extended periods of time, this is an indicator that the patient is experience progressively larger volume overload (also referred to as CV preload). When the patient's dynamic and static impedance both decrease over extended periods of time, this is an indicator that the patient is experiencing a hypovolemic state.

Next, the analysis at 182 and 184 will be described further in connection with FIGS. 2-4.

FIG. 2 illustrates a cylindrical model of the SVC and the surrounding tissue with a shocking coil located in the middle of the cylinder. The cylindrical model is useful to understand the behavior of SVC to Case impedance. Increasing volume decreased the dynamic SVC to case impedance while the stroke volume remained relatively constant. Therefore the drop in DC impedance can be confirmed with a decrease in dynamic impedance. In FIG. 2, the SVC coil 206 is conceptually located in the center of the models 202 and 204, while the case electrode 208 is located at a point along the outer perimeter of the larger cylinder. The internal cylinder 210 represents the SVC, while the outer concentric cylinder 212 represents the parts of the heart, vasculature and body outside of the SVC. For the model, the inner cylinder is assigned a resistivity value associated with blood, while the outer cylinder is assigned a resistivity value associated with tissue. The impedance between the SVC coil in the center to the periphery of the outer concentric cylinder can be calculated using typical values of blood 120 (ohm-cm) and tissue (420 ohm-cm) resistivity.

The model of FIG. 2 displays the dominant behavior of the model. The cylindrical model 202 represents the state of the SVC before volume overload, while the cylindrical model 204 represents the state of the SVC after volume overload. As one example, during volume overload the SVC diameter may increase from 1.3 to 2.4 cm, while the static impedance Zo decreases from 28.5 ohms to 25.2 ohms. The peak to peak change in impedance ΔZ=dZ may decrease from 1.2 ohms to 0.4 ohms when the emptying and filling of the cylindrical volume changes +/−2 ml under constant stroke volume conditions (also referred to as an iso-volumic state). Optionally, an increase in volume load may increase stroke volume slightly based on Starling's law. However, a modest increase in dZ caused by the increase in stroke volume would be offset by a dramatically larger decrease in dZ caused by an increase in vessel diameter (e.g., SVC, IVC or RA diameter increase).

Throughout the present specification, changes in volume of the SVC, IVC and RA are referred to as “diameter” changes. However, is it recognized that diameter represents a conceptual description of an interior dimension or distensibility used to describe volume change. While the graphs presented in connection with FIGS. 3-5 refer to diameter, other geometric parameters may also be used to describe change in the interior dimensions or distensibility of the SVC, IVC or RA relative to changes in impedance. The actual change in the diameter of the SVC, IVC or RA as measured along various planes may differ.

FIG. 3 illustrates an example of how static or DC impedance, Zo, behaves with progressive volume overload as the SVC diameter (or more generally SVC volume) increases. In FIG. 3, the horizontal axis represents SVC diameter in millimeters, while the vertical axis represents DC static impedance in ohms. As the blood volume in the inner cylinder 210 increases, the central venous pressure increases and the amount of blood surrounding the SVC coil increases. Because blood is more conductive than tissue, the DC impedance decreases. The change in impedance in the SVC is used to monitor volume overload. However, DC or static impedance alone is not very specific. In accordance with embodiments herein, dynamic impedance information is also collected and analyzed in combination with the static impedance data in order to increase the specificity of the overall determination of central venous pressure. By increasing the specificity regarding determinations of central venous pressure behavior, embodiments herein increase the clinical utility of the overall process.

FIG. 4 illustrates a graph modeling a behavior of the SVC with changes in volume overload while holding stroke volume constant. In FIG. 4, the horizontal axis represents SVC diameter (in millimeters) while the vertical axis represents changes in the peak to peak DI impedance (P-P dZ). FIG. 4 plots five different curves 402-406 corresponding to different levels of stroke volume. For example, curve 402 corresponds to a constant stroke volume of 6.25 ml, while curves 403-406 correspond to constant stroke volumes of 12.5 ml, 25 ml, 50 ml, and 100 ml, respectively. As an example, a healthy heart may exhibit a stroke volume of between 55-75 ml, or more specifically 60-70 ml. It is understood that healthy hearts may experience lower or higher stroke volumes.

FIG. 4 illustrates the behavior of dynamic impedance as measured along a vector between the SVC to Case. The peak to peak impedance dZ can be modeled as the diameter of the SVC increased with volume overload while holding stroke volume constant. As shown in FIG. 4, when stroke volume is held constant above 25 ml, the dZ Impedance drops significantly as the diameter of the SVC increases from 10 to at least 16 mm. For example, when stroke volume (also referred to as iso-stroke volume) is held constant at 100 ml, the P-P dZ decreases from 7 ohms to approximately 2 ohms as the SVC diameter decreases from 10 ml to 16 ml. As an example, the rate of change in P-P dZ relative to changes in SVC diameter may be 5 ohm per 6 mm change in SVC diameter. As the SVC diameter increases from 16 to 20 mm, the P-P dZ continues to decrease but at a lower rate (e.g., 1 ohm per 4 mm of change in SVC diameter). For curve 406, the rate of change in segments 416 and 426 changes from 5 ohm/6 mm to approximately 1 ohm/4 mm.

When stroke volume is held constant at 50 ml (curve 405), the P-P dZ decreases from 2.75 ohms to approximately 1.25 ohms as the SVC diameter increases from 10 mm to 16 mm. Hence, the segment 415 exhibits a rate of change of 1.5 ohms per 6 mm change in SVC diameter. As the SVC diameter increases from 16 to 20 mm (segment 425), the P-P dZ continues to decrease but at a lower rate (e.g., 0.5 ohm per 4 mm of change in SVC diameter). For curve 405, the rate of change in segments 415 and 425 changes from 1.5 ohm/6 mm to approximately 0.5 ohm/4 mm.

When stroke volume is held constant at 25 ml (curve 404), the P-P dZ decreases from 1.25 ohms to approximately 0.75 ohms as the SVC diameter increases from 10 mm to 16 mm. Hence, the segment 414 exhibits a rate of change of 0.5 ohms per 6 mm change in SVC diameter. As the SVC diameter increases from 16 to 20 mm (segment 424), the P-P dZ continues to decrease but at a lower rate (e.g., 0.25 ohm per 4 mm of change in SVC diameter). For curve 404, the rate of change in segments 414 and 424 changes from 0.5 ohm/6 mm to approximately 0.25 ohm/4 mm.

In comparing the illustrated curves 402-406, the curve 406 exhibits the most change in P-P dZ per unit change in SVC diameter, while the curve 405 exhibits the second largest amount of change in P-P dZ per unit change in SVC diameter. The curves 402 and 403 exhibit a similar amount of change in the P-P dZ per unit change in the SVC diameter. In curves 402 and 403, the change in P-P dZ per unit change in SVC diameter is very small as compared to the changes in curves 404-406.

From FIG. 4 it is evident that, when stroke volume is held constant above 25 ml, the change in the P-P dZ as a function of SVC diameter is very substantial and can be measured. Also, the change in the P-P dZ correlates closely to changes in the SVC diameter when measured over short ranges of SVC diameter change. The change (decrease) in P-P dZ is somewhat linear relative to increases in the SVC diameter. For example, the segments 412-416 are linear with corresponding negative slopes, while the segments 422-426 are also linear with corresponding smaller negative slopes. It is understood that the curves 402-406 are for illustration purposes only and may have different shapes that are non-linear, such as negatively sloped parabolic curves, negatively sloped polynomial slopes and the like. It is also understood that the point may change where the slope of each curve changes. For example, the slope of each curve 402-406 may change at a point greater or smaller than 16 mm of SVC diameter. However, it should be realized that the rate of change in the dZ per unit of change in SVC diameter will be greater of a portion of the range (e.g., between 10-16 mm) of change in SVC diameter.

Optionally, the curves 402-406 may exhibit more than two segments with a substantially constant slope (or small change in slope). For example, the curves 402-406 may exhibit a first slope (or range of slopes) over a segment extending from 10 to 14 mm, a second slope (or range of slopes) over a segment extending from 14-18 mm, and a third slope (or range of slopes) over a segment extending from 18 to 20 mm.

Returning to FIG. 1C, at 182, the method analysis the static VRI associated to determine whether the static VRI indicates a decrease in SI data over the persistent time POI. For example, it may be determined whether the static VRI exceeds a threshold. When the static VRI is small and does not exceed a static VRI threshold, then it is determined that, over the persistent time POI, the diameter (or generally the interior dimensions) of the SVC, IVC or RA have not enlarged unduly. When the diameter remains relatively constant or within an acceptable tolerance range, then the method need not analyze the DI data (or dynamic VRI) for persistent changes in dynamic impedance.

Alternatively, when it is determined that the static VRI exceeds a static VRI threshold, then the method determines that, over the persistent time POI, the diameter (or generally the interior dimensions) of the SVC, IVC or RA have enlarged unduly. When the diameter enlarges beyond an acceptable tolerance range, then the method continues by analyzing the DI data (or dynamic VRI) for persistent changes in dynamic impedance. As one example, the static VRI threshold may be set based on shapes of the dZ-SVC and/or dZ-SVC curves (FIGS. 4-5).

At 184, the method analyzes the dynamic and static VRI over a select short period of time (relative to the time period in 182) to obtain short-term variation (STV) or transient information regarding changes and trends in the DI and SI data. For example, the short or transient period of time may be 5 minutes, 10-20 minutes, less than an hour and the like.

At 186, the method analyzes the STV information to determine whether short-term trends are indicated. Short term trend information is useful at least in connection with determining how stroke volume is affected by different IMD therapy parameter settings. For example, over a 20 minute or 1 hour short term test period, 5 different IMD therapy parameter settings may be used (e.g., 120 msec, 140 msec, 160 msec, 180 msec and 200 msec), while corresponding DI and SI data measurements are collected. The STV information may indicate that, over the test period, the patient's dynamic impedance was largest when the AV delay was 180 msec, but progressively decreased as the AV delay setting was decreased to 140 msec and was lower as well at 200 msec. When the STV information indicates that the patient's dynamic impedance has a local maximum, this is an indicator that the stroke volume (associated with different IMD therapy parameter settings) was greatest at 180 msec.

Other examples of indicators afforded by changes in short term variation, optimize VV timing or selecting between one or combinations of the quad-pole electrodes, an indicator of hemodynamic reserve. Hemodynamic reserve represents a function of contractility, venous return and total peripheral resistance.

At 190, the method analyzes the LTV information to determine whether long-term trends are indicated. Long term trend information is useful at least in connection with determining whether volume overload is present and if so, whether different IMD therapy parameter settings affect the volume overload. For example, over a 2 week or 1 month long term test period, 5 different IMD therapy parameter settings may be used (e.g., 150 msec, 175 msec, 200 msec, 225 msec and 250 msec), while corresponding DI and SI data measurements are collected. The LTV information may indicate that, over the long term test period, the patient's dynamic and static impedance was largest when the AV delay was 200 msec, but progressively decreased at the other AV delay setting. When the LTV information indicates that the patient's dynamic and static impedance has a local maximum, this is an indicator that the associated IMD therapy parameter settings resulted in the least volume overload. Hence, at 190, the IMD therapy parameter settings may be set with an AV delay of 200 msec in the present example.

In accordance with embodiments herein, methods and systems are described that measure and analyze the decrease in P-P dZ (DI data) along with decreases in Zo (SI data) to validate a presence of volume overload. As explained herein, the dZ may be measured throughout the day or when the patient is laying down to filter out the effects of posture on preload.

FIG. 5 illustrates graphs modeling a behavior of stroke volume for different fixed/constant SVC diameters (corresponding to different constant volume overloads. In FIG. 5, the horizontal axis represents stroke volume (in milliliters), while the vertical axis represents changes in the P-P dZ. FIG. 5 plots three different curves 502-504 corresponding to different levels of fluid overload (each of which has a corresponding constant SVC diameter). For example, curve 402 corresponds to a constant SVC diameter of 10 mm, while curves 403-404 correspond to constant SVC diameters of 16 mm and 20 mm, respectively. As an example, a healthy heart may exhibit a stroke volume of between 10 and 16 mm, or more specifically 10-14 mm. It is understood that healthy hearts may experience lower or higher SVC diameters.

FIG. 5 shows that while the diameter of the SVC remains substantial constant, the dynamic impedance increases with increasing stroke volume during an individual cardiac cycle. This allows for stoke volume measurement during constant SVC diameter states (also referred to as iso-preload states). The direct correlation between P-P dZ and stroke volume, while in an iso-preload state, is utilized in accordance with embodiments here monitor stroke volume and to adjust device settings to achieve a desired level of SV. For example, the device settings (therapy parameters) that may be adjusted may include one or more of AV delay, V-V timing, and the selection of which combination of electrodes are used to deliver therapy. The device therapy parameters may be adjusted until a desired SV level is achieved as long as preload remains generally constant or within a predetermined tolerance range.

In accordance with certain embodiments, when it is desirable to adjust device therapy parameters based on the relations illustrated in FIG. 5 to achieve a desired SV level, it is desirable to maintain a stable iso-preload state and a stable posture. For example, the stable iso-preload state may represent a constant SVC diameter or an SVC diameter that is maintained within a predetermined range or percentage of variation from a baseline SVC diameter.

Returning to FIGS. 4 and 5, as shown in FIG. 4, variation in dZ may be due to changes in SVC diameter (also referred to as a variable preload state) when SV is constant. Yet, as shown in FIG. 5, variation in dZ may be due to changes in SV (also referred to as a variable SV state) when SVC diameter is constant. Hence, embodiments herein collect DI data over different time periods and for different numbers of successive cardiac cycles in order to obtain a collection of DI data from which subsets of DI data may be accessed and analyzed to determine different characteristics of fluid status in the central venous region.

Embodiments herein account for the potential that activity and posture may constantly modulate preload such that DI and SI data collected along one or more impedance vectors such as the SVC to case vector may be used to achieve a desired level for SV.

Optionally, in certain subjects, it may be desirable to change the IMD therapy parameters to achieve a desired level for the diastolic function and increase the diastolic time while increasing the contractility. An affect of set values for the IMD therapy parameters can be identified through the DI morphology of the dynamic impedance data. As an example, a DI morphology can be stored as a profile and the slope and timing from the DI morphology can be used for optimization to tailor the IMD therapy parameters for a given subject.

FIG. 6 illustrates a block diagram of the IMD 10, which is capable of performing the methods described herein and of treating one or both of fast and slow arrhythmias with stimulation therapy, including cardioversion, defibrillation, and pacing stimulation. While a particular multi-chamber device is shown, this is for illustration purposes only. It is understood that the appropriate circuitry could be duplicated, eliminated or disabled in any desired combination to provide a device capable of simply monitoring impedance and/or cardiac signals, and/or treating the appropriate chamber(s) with cardioversion, defibrillation and pacing stimulation.

The housing 40 for the stimulation IMD 10 is often referred to as the “can”, “case” or “case electrode” and may be programmably selected to act as the return electrode for some or all sensing modes. The housing 40 may further be used as a return electrode alone or in combination with one or more of the electrodes of FIG. 1 for shocking purposes. The housing 40 further includes a connector (not shown) having a plurality of terminals 41-52. To achieve sensing, pacing and shocking in desired chambers of the heart, the terminals 41-52 are selectively connected to corresponding combinations of electrodes 22-38.

The IMD 10 includes a programmable microcontroller 60 that controls the various modes of sensing and stimulation therapy. The microcontroller 60 includes a microprocessor, or equivalent control circuitry, designed specifically for controlling sensing impedance derivation and the delivery of stimulation therapy and may further include RAM or ROM memory, logic and timing circuitry, state machine circuitry, and I/O circuitry. The microcontroller 60 includes the ability to process or monitor input signals (data) as controlled by a program code stored in memory. The details of the design and operation of the microcontroller 60 are not critical to the present invention. Rather, any suitable microcontroller 60 may be used.

The microcontroller 60 may search for a pacing threshold following paced events. The microcontroller 60 may do so by performing an auto capture process to determine whether a paced event successfully captured the surrounding tissue. The microcontroller 60 includes an arrhythmia detection module 75 that analyzes sensed signals and determines when an arrhythmia (e.g., fibrillation) is occurring. The detection module 75 receives signals sensed by electrodes located at sensing sites. The detection module 75 detects arrhythmias, such as ventricular tachycardia (VT), bradycardia and ventricular fibrillation (VF). The microcontroller 60 may include a morphology detection module (not shown) that analyzes the morphology of the cardiac signal. Among other things, the module may detect R wave peaks, P wave peaks and/or detect T wave features of interest, such as onset, peak, etc.

The microcontroller 60 includes inputs that are configured to collect cardiac signals associated with electrical or mechanical behavior of a heart over at least one cardiac cycle. The cardiac signals may IEGM signals from the atrial or ventricular sensing circuits 82 and 84 that are representative of electrical behavior of the heart. Optionally, the cardiac signals may be the output of the A/D circuit 90 that are representative of electrical behavior of the heart. The cardiac signals may be the output of the physiologic sensor 108 that are representative of mechanical behavior. As one example, the inputs are configured to collect the DI data utilizing an IMD case electrode and at least one of an SVC electrode, an IVC electrode and an RA electrode to define the VR vector.

The inputs are also configured to receive dynamic impedance (DI) data and static impedance (SI) data that are collected over multiple cardiac cycles (CC) for a persistent time period of interest (POI). The DI and SI data is collected along a central venous (CV) vector that extends through a superior vena cava (SVC).

The microcontroller 60 includes a CS module 70, a DI module 71, an MC module 72, a therapy module 73 and an arrhythmia detection module 75 (among other things). The cardiac signal (CS) module 70 is configured to identify a timing feature of interest (FOI) from the cardiac signals.

The DI module 71 is configured to collect dynamic impedance (DI) data over at least one cardiac cycle, designated by the timing FOI, along at least one of i) a venous return vector or ii) a right ventricular function vector.

The morphology characteristic (MC) module 72 is configured to analyze at least one morphologic characteristic from the DI data based on at least one of a CV-DI correlation metric to obtain a CV indicator associated with the CC. The MC module 72 is further configured to determine a select level for the at least one therapy parameter that provides at least one of i) a select peak to peak amplitude, ii) a select minimum amplitude, iii) a select DI change per unit time, iv) a select slope, v) a select ventricular filling time, or vi) a select ventricular emptying time, of the DI data when plotted over time. The MC module 72 is configured to determine, as the morphologic characteristic, at least one of i) a peak to peak amplitude, ii) a minimum amplitude, iii) a minimum DI change per unit time, iv) slope, v) a select ventricular filling time, or vi) a select ventricular emptying time, of the DI data over the CC. The MC module 72 collects and analyzes the DI data in connection with a select activity state and a select posture position of a patient.

The therapy module 73 is configured to modulate, over multiple cardiac cycles, at least one therapy parameter while the IMD 10 obtains a collection of CV indicators associated with different therapy parameters. The therapy module 73 is configured to adjust a therapy configuration based on the collection of CV indicators, such that the system operates to encourage a select CV level.

The memory 94 stores correlation metrics associated with the cardiac functions of interest, such as CV-DI correlation metrics. The CV-DI correlation metric represents at least one of i) a relation between changes in the P-P amplitude and changes in stroke volume and contractile strength, and ii) a relation between changes in the slope of the DI data and changes in direction and degree of cardiac contractility.

The memory 94 also stores the CV indicators and associated IMD therapy parameter values for each iteration through the methods of FIGS. 1B and 6. Once the IMD 10, system or method determines a new set of IMD therapy parameter values to be used to encourage a select VR or RVF level.

The microcontroller 60 further includes an impedance analysis module 83 and a trend detection module 85. The impedance analysis (IA) module 83 is configured to analyze the DI and SI data, collected over the persistent time POI, to obtain DI long-term variation (LTV) information and SI LTV information, respectively. The trend detection (TD) module 85 is configured to detect when the DI LTV information and the SI LTV information include decreasing persistent trends in the DI and SI data. The trend detection module 85 is configured to generate an overload output indicating that the heart is experiencing volume overload when the trend detection module detects the decreasing persistent trend in the DI and SI data.

The DI and SI data represent a surrogate for central venous pressure such that when the trend detection module detects the decreasing persistent trend. As explained above, the fluid status in the CV system corresponds to a volume overload state. The overload output indicates that an interior dimension of the SVC is expanding over the LT time period of interest by more than a predetermined CV expansion threshold. The analysis module 83 is further configured to analyze at least one morphologic characteristic from the DI and SI data to obtaining DI and SI central venous (CV) indicators for each cardiac cycle, the DI and SI CV indicators representative of a feature of interest within the DI and SI data, respectively; and analyze the DI and SI indicators to obtain the LTV information. As explained above, the DI LTV information corresponds to changes in dynamic impedance over the persistent time period of interest that extends over at least one of hours, days or weeks. The analysis module 83 is further configured to analyze the DI and SI data, collected over a transient time period of interest, to obtain DI short-term variation (STV) information. The trend detection module 85 is further configured to determine whether the DI STV information includes an increasing or decreasing ST trend in the DI data, when a decreasing ST trend exists in the DI data, the trend detection module configured to generate a stroke volume (SV) output indicating that the heart is experiencing a decrease in stroke volume.

The therapy control module 73 is configured to change at least one IMD therapy parameter setting, over multiple cardiac cycles, and repeat the collecting, analyzing and detecting operations to obtain a collection of DI LTV information and the SI LTV information associated with different IMD therapy parameter settings. The therapy control module 73 may determine, based on the overload output, a select level for the at least one IMD therapy parameter setting that provides at least one of i) a select peak to peak amplitude, ii) a select minimum amplitude, iii) a select DI change per unit time (dZ/dt), iv) a select slope, v) a select ventricular filling time, or vi) a select ventricular emptying time, of the DI data when plotted over time. The analysis module 83 is configured to analyze the DI data by determining, as a morphologic characteristic, at least one of i) a peak to peak (P-P) amplitude, ii) a minimum amplitude, iii) a minimum DI change per unit time (dZ/dt), and iv) slope of the DI data over the CC.

Optionally, the analysis module 83 is configured to determine receive patient state information indicating at least one of a select activity state and a select posture position of a patient, the analysis module configured to control the inputs to collect the DI data only when the patient state information satisfies a patient state threshold.

An atrial pulse generator 70 and a ventricular pulse generator 72 generate pacing and ATP stimulation pulses for delivery by desired electrodes. The electrode configuration switch 74 (also referred to as switch bank 74) controls which terminals 41-52 receive shocks or pacing pulses. The atrial and ventricular pulse generators, 70 and 72, may include dedicated, independent pulse generators, multiplexed pulse generators, shared pulse generators or a single common pulse generator. The pulse generators 70 and 72 are controlled by the microcontroller 60 via appropriate control signals 76 and 78, respectively, to trigger or inhibit stimulation pulses. The microcontroller 60 further includes timing control circuitry 79 which is used to control the timing of such stimulation pulses (e.g., pacing rate, atrio-ventricular (AV) delay, atrial interconduction (A-A) delay, or ventricular interconduction (V-V) delay, etc.) as well as to keep track of the timing of refractory periods, PVARP intervals, noise detection windows, evoked response windows, alert intervals, marker channel timing, etc.

An electrode configuration switch 74 connects the sensing electronics to the desired terminals 41-52 of corresponding sensing electrodes 22-38. For example, terminals 49-52 may be coupled to LV electrodes 23-26. The switch 74 may connect terminals 41-52 to one or more ventricular sensing circuits 84, which provide cardiac signals, representative of cardiac activity, to the microcontroller. The circuit 84 may amplify, filter, digitize and/or otherwise process the sensed cardiac signals from the LV electrodes 23-26. The circuit 84 may provide separate, combined or difference signals to the microcontroller 60 representative of the sensed signals from the LV electrodes 23-26. The circuit 84 may also receive sensed signals from RV electrodes 32 and 34 through terminals 43 and 44. The atrial sensing circuit 82 is connected through the switch 74 terminals 42 and 45-46 to desired RA and/or LA electrodes 22 and 27-28 to sense RA and/or LA cardiac activity. The switch 74 also connects various combinations of the electrodes 22-38 to an impedance measurement circuit 113.

An impedance measuring circuit 112 includes inputs to collect multiple measured impedances between corresponding multiple combinations of electrodes 22-38. For example, the impedance measuring circuit 112 may collect a measured impedance for each or a subset of the active sensing vectors 151-155. Optionally, the impedance measuring circuit 112 may also monitor lead impedance during the acute and chronic phases for proper lead positioning or dislodgement; detects operable electrodes and automatically switches to an operable pair if dislodgement occurs; measures respiration or minute ventilation; measures thoracic impedance for determining shock thresholds; detects when the device has been implanted; measures stroke volume; and detects the opening of heart valves, etc.

The switch bank 74 includes a plurality of switches for connecting the desired electrodes to the appropriate I/O circuits, thereby providing complete electrode programmability. The switch 74, in response to a control signal 80 from the microcontroller 60, determines the polarity of the stimulation pulses (e.g., unipolar, bipolar, co-bipolar, etc.) by selectively closing the appropriate combination of switches (not specifically shown). Atrial sensing circuits 82 and ventricular sensing circuits 84 may also be selectively coupled to the right atrial lead 20, LV lead 21, and the RV lead 30, through the switch 74 for detecting the presence of cardiac activity in each of the four chambers of the heart. The switch 74 determines the “sensing polarity” of the cardiac signal by selectively closing the appropriate switches.

The outputs of the atrial and ventricular sensing circuits 82 and 84 are connected to the microcontroller 60 that, in turn, is able to trigger or inhibit the atrial and ventricular pulse generators 70 and 72, respectively. The sensing circuits 82 and 84, in turn, receive control signals over signal lines 86 and 88 from the microcontroller 60 for purposes of controlling the gain, threshold, the polarization charge removal circuitry (not shown), and the timing of any blocking circuitry (not shown) coupled to the inputs of the sensing circuits, 82 and 86.

Cardiac signals are also applied to the inputs of an analog-to-digital (ND) data acquisition system 90. The data acquisition system 90 is configured to acquire intracardiac electrogram signals, convert the raw analog data into a digital signal, and store the digital signals for later processing and/or telemetric transmission to an external IMD 10. The data acquisition system 90 samples cardiac signals across any pair of desired electrodes. The data acquisition system 90 may be coupled to the microcontroller 60, or other detection circuitry, for detecting an evoked response from the heart 12 in response to an applied stimulus, thereby aiding in the detection of “capture.” Capture occurs when an electrical stimulus applied to the heart is of sufficient energy to depolarize the cardiac tissue, thereby causing the heart muscle to contract.

The microcontroller 60 is further coupled to a memory 94 by a suitable data/address bus 96. The memory 94 stores programmable operating, impedance measurements, impedance derivation and therapy-related parameters used by the microcontroller 60. The operating and therapy-related parameters define, for example, pacing pulse amplitude, pulse duration, electrode polarity, rate, sensitivity, automatic features, arrhythmia detection criteria, and the amplitude, wave shape and vector of each stimulating pulse to be delivered to the patient's heart 12 within each respective tier of therapy.

The impedance derivation parameters may include information designating i) sensing electrodes to use to define active sensing vectors, ii) sets and subsets of sensing vectors to use to monitor various regions of the heart, iii) sets or subsets of active sensing vectors to combine to form each pseudo sensing vector, iv) weight valves to use with active sensing vectors to form each pseudo sensing vector, v) algorithms for how to mathematically combine active sensing vectors to form each pseudo sensing vector, and the like.

The operating and therapy-related parameters may be non-invasively programmed into the memory 94 through a telemetry circuit 100 in telemetric communication with the external IMD 10, such as a programmer, trans-telephonic transceiver, or a diagnostic system analyzer. The telemetry circuit 100 is activated by the microcontroller 60 by a control signal. The telemetry circuit 100 advantageously allows intracardiac electrograms and status information relating to the operation of the IMD 10 (as contained in the microcontroller 60 or memory 94) to be sent to the external device 101 through an established communication link 103.

The microcontroller 60 includes an impedance derivation module 77 that derives impedances associated with pseudo sensing vectors based on impedance measurements along active sensing vectors. The impedance derivation module 77 performs the operations discussed herein in connection with FIG. 6.

The stimulation IMD 10 may include a physiologic sensor 107 to adjust pacing stimulation rate according to the exercise state of the patient. The physiological sensor 107 may further be used to detect changes in cardiac output, changes in the physiological condition of the heart, or diurnal changes in activity (e.g., detecting sleep and wake states). The battery 111 provides operating power to all of the circuits shown.

The microcontroller 60 further controls a shocking circuit 117 by way of a control signal. The shocking circuit 117 generates stimulating pulses of low (up to 0.5 Joules), moderate (0.5-10 Joules), or high energy (11 to 40 Joules), as controlled by the microcontroller 60. Stimulating pulses are applied to the patient's heart 12 through at least two shocking electrodes, and as shown in this embodiment, selected from the left atrial (LA) coil electrode 28, the RV coil electrode 36, the SVC coil electrode 38 and/or the housing 40.

FIG. 7 illustrates a functional block diagram of the external device 1000 that is operated in accordance with the processes described herein and to interface with implantable medical devices as described herein. The external device 1000 is configured to perform all or a portion of the operations described herein. For example, the external device may perform all or a portion of the operations in FIGS. 1B and 1C. For example, the external device 1000 may include all or a portion of the modules in the microcontroller 60 described in connection with FIG. 6. For example, the external device 1000 may include inputs to collect cardiac signals and DI data, as well as one or more of a CS module, DI module, MC module, therapy module, impedance analysis module, and trend detection module configured to perform the operations described above.

The external device 1000 may be a workstation, a portable computer, an IMD programmer, a PDA, a cell phone and the like. The external device 1000 includes an internal bus that connects/interfaces with a Central Processing Unit (CPU) 1002, ROM 1004, RAM 1006, a hard drive 1008, the speaker 1010, a printer 1012, a CD-ROM drive 1014, a floppy drive 1016, a parallel I/O circuit 1018, a serial I/O circuit 1020, the display 1022, a touch screen 1024, a standard keyboard connection 1026, custom keys 1028, and a telemetry subsystem 1030. The internal bus is an address/data bus that transfers information between the various components described herein. The hard drive 1008 may store operational programs as well as data, such as waveform templates and detection thresholds.

The CPU 1002 typically includes a microprocessor, a micro-controller, or equivalent control circuitry, designed specifically to control interfacing with the external device 1000 and with the IMD 100. The CPU 1002 performs the COI measurement process discussed above. The CPU 1002 may include RAM or ROM memory, logic and timing circuitry, state machine circuitry, and I/O circuitry to interface with the IMD 100. The display 1022 (e.g., may be connected to the video display 1032). The touch screen 1024 may display graphic information relating to the IMD 100. The display 1022 displays various information related to the processes described herein. The touch screen 1024 accepts a user's touch input 1034 when selections are made. The keyboard 1026 (e.g., a typewriter keyboard 1036) allows the user to enter data to the displayed fields, as well as interface with the telemetry subsystem 1030. Furthermore, custom keys 1028 turn on/off 1038 (e.g., EVVI) the external device 1000. The printer 1012 prints copies of reports 1040 for a physician to review or to be placed in a patient file, and speaker 1010 provides an audible warning (e.g., sounds and tones 1042) to the user. The parallel I/O circuit 1018 interfaces with a parallel port 1044. The serial I/O circuit 1020 interfaces with a serial port 1046. The floppy drive 1016 accepts diskettes 1048. Optionally, the floppy drive 1016 may include a USB port or other interface capable of communicating with a USB device such as a memory stick. The CD-ROM drive 1014 accepts CD ROMs 1050.

The telemetry subsystem 1030 includes a central processing unit (CPU) 1052 in electrical communication with a telemetry circuit 1054, which communicates with both an IEGM circuit 1056 and an analog out circuit 1058. The circuit 1056 may be connected to leads 1060. The circuit 1056 is also connected to the implantable leads 114, 116 and 118 to receive and process IEGM cardiac signals as discussed above. Optionally, the IEGM cardiac signals sensed by the leads 114, 116 and 118 may be collected by the IMD 100 and then transmitted, to the external device 1000, wirelessly to the telemetry subsystem 1030 input.

The telemetry circuit 1054 is connected to a telemetry wand 1062. The analog out circuit 1058 includes communication circuits to communicate with analog outputs 1064. The external device 1000 may wirelessly communicate with the IMD 100 and utilize protocols, such as Bluetooth, GSM, infrared wireless LANs, HIPERLAN, 3G, satellite, as well as circuit and packet data protocols, and the like. Alternatively, a hard-wired connection may be used to connect the external device 1000 to the IMD 100.

It is to be understood that the above description is intended to be illustrative, and not restrictive. For example, the above-described embodiments (and/or aspects thereof) may be used in combination with each other. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from its scope. While the dimensions, types of materials and coatings described herein are intended to define the parameters of the invention, they are by no means limiting and are exemplary embodiments. Many other embodiments will be apparent to those of skill in the art upon reviewing the above description. The scope of the invention should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Moreover, in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects. Further, the limitations of the following claims are not written in means—plus-function format and are not intended to be interpreted based on 35 U.S.C. §112, sixth paragraph, unless and until such claim limitations expressly use the phrase “means for” followed by a statement of function void of further structure. 

What is claimed is:
 1. A method for determining fluid status with a central venous system of a heart, the method comprising: collecting dynamic impedance (DI) data and static impedance (SI) data over multiple cardiac cycles (CC) for a persistent time period of interest (POI), the DI and SI data collected along a central venous (CV) vector that extends through a superior vena cava (SVC); analyzing the DI and SI data, collected over the persistent time POI, to obtain DI long-term variation (LTV) information and SI LTV information, respectively; detecting whether the DI LTV information and the SI LTV information include decreasing persistent trends in the DI and SI data; and when decreasing persistent trends are detected in the DI and SI data, generating an overload output indicating that the heart is experiencing a volume overload state.
 2. The method of claim 1, wherein the DI and SI data represent a surrogate for central venous pressure such that when a decreasing persistent trend is detected a fluid status corresponds to the volume overload state.
 3. The method of claim 1, wherein the overload output indicates that an interior dimension of the SVC is expanding over the LT time period of interest.
 4. The method of claim 1, wherein the analyzing operation further comprises: analyzing at least one morphologic characteristic from the DI and SI data to obtaining DI and SI central venous (CV) indicators for each cardiac cycle, the DI and SI CV indicators representative of a feature of interest within the DI and SI data, respectively; and analyzing the DI and SI indicators to obtain the LTV information.
 5. The method of claim 1, wherein the DI LTV information corresponds to changes in dynamic impedance over the persistent time period of interest that extends over at least one of hours, days or weeks.
 6. The method of claim 1, further comprising: analyzing the DI and SI data, collected over a transient time period of interest, to obtain DI short-term variation (STV) information; determining whether the DI STV information includes an increasing or decreasing ST trend in the DI data; and when a decreasing ST trend exists in the DI data, generating a stroke volume (SV) output indicating that the heart is experiencing a decrease in stroke volume.
 7. The method of claim 1, further comprising, over multiple cardiac cycles, changing at least one IMD therapy parameter setting and repeating the collecting, analyzing and detecting operations to obtain a collection of DI LTV information and the SI LTV information associated with different IMD therapy parameter settings.
 8. The method of claim 1, further comprising, based on the overload output, determining a select level for the at least one IMD therapy parameter setting that provides at least one of i) heart rate paced, ii) pacing mode (options include DDD, DOO, VVI, VOO, AAI and AOO), iii) a select peak to peak amplitude, iv) a select minimum amplitude, v) a select DI change per unit time (dZ/dt), vi) a select slope, vii) a select ventricular filling time, or viii) a select ventricular emptying time, of the DI data when plotted over time.
 9. The method of claim 1, wherein the collecting of DI data includes utilizing an IMD case electrode and at least one of an SVC electrode, an IVC electrode and an RA electrode to define the CV vector and to collect the DI and SI data.
 10. The method of claim 1, wherein the analyzing the DI data includes determining, as a morphologic characteristic, at least one of i) a peak to peak (P-P) amplitude, ii) a minimum amplitude, iii) a minimum DI change per unit time (dZ/dt), iv) slope and v) area under the curve, vi) time features from fiducial points of the DI data over the CC.
 11. The method of claim 1, wherein the CV vector extends through at least one of the SVC, RA or IVC.
 12. A system for determining fluid status with a central venous system of a heart, the system comprising: inputs configured to receive dynamic impedance (DI) data and static impedance (SI) data that is collected over multiple cardiac cycles (CC) for a persistent time period of interest (POI), the DI and SI data collected along a central venous (CV) vector that extends through a superior vena cava (SVC); an impedance analysis (IA) module configured to analyze the DI and SI data, collected over the persistent time POI, to obtain DI long-term variation (LTV) information and SI LTV information, respectively; and a trend detection (TD) module configured to detect when the DI LTV information and the SI LTV information include decreasing persistent trends in the DI and SI data, the trend detection module configured to generate an overload output indicating that the heart is experiencing volume overload when the trend detection module detects the decreasing persistent trend in the DI and SI data.
 13. The system of claim 12, wherein the DI and SI data represent a surrogate for central venous pressure such that when the trend detection module detects the decreasing persistent trend, a fluid status in the CV system corresponds to a volume overload state.
 14. The system of claim 12, wherein the overload output indicates that an interior dimension of the SVC is expanding over the LT time period of interest by more than a predetermined CV expansion threshold.
 15. The system of claim 12, wherein the analysis module is further configured to: analyze at least one morphologic characteristic from the DI and SI data to obtaining DI and SI central venous (CV) indicators for each cardiac cycle, the DI and SI CV indicators representative of a feature of interest within the DI and SI data, respectively; and analyze the DI and SI indicators to obtain the LTV information.
 16. The system of claim 12, wherein the DI LTV information corresponds to changes in dynamic impedance over the persistent time period of interest that extends over at least one of hours, days or weeks.
 17. The system of claim 12, whether the analysis module is further configured to analyze the DI and SI data, collected over a transient time period of interest, to obtain DI short-term variation (STV) information; and the trend detection module is further configured to determine whether the DI STV information includes an increasing or decreasing ST trend in the DI data, when a decreasing ST trend exists in the DI data, the trend detection module configured to generate a stroke volume (SV) output indicating that the heart is experiencing a decrease in stroke volume.
 18. The system of claim 12, further comprising a therapy control module configured to change at least one IMD therapy parameter setting, over multiple cardiac cycles, and repeat the collecting, analyzing and detecting operations to obtain a collection of DI LTV information and the SI LTV information associated with different IMD therapy parameter settings.
 19. The system of claim 12, further comprising a therapy control module configured to determine, based on the overload output, a select level for the at least one IMD therapy parameter setting that provides at least one of i) heart rate paced, ii) pacing mode (options include DDD, DOO, VVI, VOO, AAI and AOO), iii) a select peak to peak amplitude, iv) a select minimum amplitude, v) a select DI change per unit time (dZ/dt), vi) a select slope, vii) a select ventricular filling time, or viii) a select ventricular emptying time, of the DI data when plotted over time.
 20. The system of claim 12, further comprising a lead coupled to the inputs, the lead including an IMD case electrode and at least one of an SVC electrode, an IVC electrode and an RA electrode to define the CV vector and to collect the DI and SI data.
 21. The system of claim 12, wherein the analysis module is configured to analyze the DI data by determining, as a morphologic characteristic, at least one of i) a peak to peak (P-P) amplitude, ii) a minimum amplitude, iii) a minimum DI change per unit time (dZ/dt), iv) slope v) area under the curve, and vi) time features from fiducial points of the DI data over the CC.
 22. The system of claim 12, wherein the analysis module is configured to receive patient state information indicating at least one of a select activity state and a select posture position of a patient, the analysis module configured to control the inputs to collect the DI data only when the patient state information satisfies a patient state threshold. 